Offsite Construction Projects Research Articles

Building an Information Modeling-Based System for Automatically Generating the Assembly Sequence of Precast Concrete Components Using a Genetic Algorithm

Facing a significant decrease in economic working processes, Off-Site Construction (OSC) methods have been frequently adopted in response to challenges such as declining productivity and labor shortages in the construction industry. Currently, in most OSC applications, the assembly phase is traditionally managed based on the personal experience and judgment of the site managers. This approach can lead to inaccuracies or omissions, particularly when dealing with a large amount of information on large, complex construction sites. Additionally, there are limitations in exploring more efficient and productive alternatives for rapidly adapting to changing on-site conditions. Given that the assembly phase significantly affects the OSC productivity, a systematic management approach is crucial for expanding OSC methods. Some initial studies used computer algorithms to determine the optimal assembly sequences. However, these studies often focused on geometrical characteristics, such as component weight or spatial occupancy, neglecting crucial factors in actual site planning, such as the work radius and component installation status. Moreover, these studies tended to prioritize the generation of initial assembly sequences rather than providing alternatives for adapting to evolving on-site conditions. In response to these limitations, this study presents a systematic framework utilizing a Building Information Modeling (BIM)–Genetic Algorithm (GA) approach to generate Precast Concrete (PC) component installation sequences. The developed system employs Genetic Algorithms to objectively explore diverse assembly plans, emphasizing the flexibility of accommodating evolving on-site conditions. Real on-site scenarios were simulated using this framework to explore multiple assembly plan alternatives and validate their applicability. Comprehensive interviews were conducted to validate the research and confirm the system’s potential contributions, especially at just-in-time-focused PC sites. Acknowledging a broader range of variables such as equipment and manpower, this study anticipates fostering more systematic on-site management within the context of a digitized construction environment. The proposed algorithm contributes to improving both productivity and sustainability of the construction industry by optimizing the management process of the off-site construction projects.

Group technology empowering optimization of mixed-flow precast production in off-site construction.

Faced with immense pressure to reduce environmental impact, off-site construction (OSC) is considered a sustainable alternative to conventional practices. However, challenged by component diversity and a significant surge in demand, deficient or empirical-based scheduling management struggles to effectively harness the potential of mixed-flow precast production to improve efficiency, instead resulting in environmental impacts, and falling short of expected benefits in OSC projects. Therefore, this study addresses the conflict between efficiency and environmental impact arising from the application of mixed-flow precast production by integrating multi-objective optimization and group technology. A multi-objective optimization framework is proposed, incorporating grouping technology for mixed-flow precast production scheduling and aiming to minimize carbon emissions and reduce tardiness/earliness penalty. The non-dominated sorting genetic algorithm II (NSGA-II), adjusted by adaptive population initialization strategy and group technology, is introduced to solve this problem, striking a balance between sustainability and penalty costs. Through a real-case analysis, the proposed approach demonstrates an average reduction of 37.5% in carbon emissions compared to rule-based scheduling methods, a 30.1% reduction compared to previous research methods, along with over 10% reduction in tardiness/earliness penalty. This study enhances environmental benefits and efficiency from a production scheduling perspective and establishes an automated, practical method, fostering low-cost, high-efficiency green production for construction component enterprises, particularly for small and medium-sized enterprises, thereby promoting sustainable development in the construction industry.

Shaping online and offline informal learning networks in off-site construction projects: a proximity perspective

PurposeInformal learning networks are critical to response to calls for practitioners to reskill and upskill in off-site construction projects. With the transition to the coronavirus disease 2019 (COVID-19) pandemic, social media-enabled online knowledge communities play an increasingly important role in acquiring and disseminating off-site construction knowledge. Proximity has been identified as a key factor in facilitating interactive learning, yet which type of proximity is effective in promoting online and offline knowledge exchange remains unclear. This study takes a relational view to explore the proximity-related antecedents of online and offline learning networks in off-site construction projects, while also examining the subtle differences in the networks' structural patterns.Design/methodology/approachFive types of proximity (physical, organizational, social, cognitive and personal) between projects members are conceptualized in the theoretical model. Drawing on social foci theory and homophily theory, the research hypotheses are proposed. To test these hypotheses, empirical case studies were conducted on two off-site construction projects during the COVID-19 pandemic. Valid relational data provided by 99 and 145 project members were collected using semi-structured interviews and sociometric questionnaires. Subsequently, multivariate exponential random graph models were developed.FindingsThe results show a discrepancy arise in the structural patterns between online and offline learning networks. Offline learning is found to be more strongly influenced by proximity factors than online learning. Specifically, physical, organizational and social proximity are found to be significant predictors of offline knowledge exchange. Cognitive proximity has a negative relationship with offline knowledge exchange but is positively related to online knowledge exchange. Regarding personal proximity, the study found that the homophily effect of hierarchical status merely emerges in offline learning networks. Online knowledge communities amplify the receiver effect of tenure. Furthermore, there appears to be a complementary relationship between online and offline learning networks.Originality/valueProximity offers a novel relational perspective for understanding the formation of knowledge exchange connections. This study enriches the literature on informal learning within project teams by revealing how different types of proximity shape learning networks across different channels in off-site construction projects.

Identifying Critical Risk Factors and Management Activities for Effective Offsite Construction Projects during Construction Phase

Off-site construction (OSC) has been drawing attention as a solution to the internal and external problems that the construction industry is facing. This study identified and analyzed the critical risk factors and activities to manage during OSC project execution, including production, transportation, assembly, and integration. Twelve critical risk factors and 50 management activities were derived from the existing literature. OSC experts scored each attribute’s importance and performance, and reliability was tested with Cronbach’s alpha. Results represented by an importance and performance analysis (IPA) matrix showed low performance and high importance of OSC projects. Poor human resources management had the highest importance, whereas lifting error had the highest performance. Production planning error ranked lowest in both importance and performance. Hence, OSC projects need to improve performance further, and intensive management should be used to minimize the performance–importance imbalance.

Cloud-based information system for automated precast concrete transportation planning

Transportation planning of precast concrete (PC) products require a large amount of information to be integrated and communicated among the managers. However, without a system specialized for PC products transportation planning, they currently have difficulties in generating and communicating the plans quickly and efficiently. This study proposes a cloud-based information system for automated PC transportation planning. Specifically, the authors first identified 26 functional requirements based on a PC transportation planning process analysis, literature review, and expert interviews. The authors then designed five system modules and a system architecture that can meet the requirements. The authors validated the system design by developing a prototype and testing its utility and applicability through a case study and demonstration to experts. This study provides knowledge on the requirements of PC transportation planning systems and a system design that can resolve PC logistics problems, which can contribute to improving the productivity of offsite construction projects.

Development of offsite construction skill profile prediction models using mixed-effect regression analysis

Offsite construction (OSC) transfers onsite construction activities to factory-based processes utilising technological advancements, resulting in new and emerging skills while causing some existing skills to be changed and others to be redundant. However, there are no established methods to systematically quantify these OSC skill requirements. This paper presents OSC skill prediction models while highlighting the process of model development for future research. The aim of these models is to predict skills using a comparable measure, manhours/m2. A skill classification with six skill categories was used to analyse OSC skills. Numerical model development methods were reviewed, and mixed-effect regression modelling was selected for model development. The skills data needed for regression modelling was collected using eight case studies. Predominantly panelised and modular OSC projects were used to collect skills data. The skill prediction models were validated using further case study data and an expert forum. Comparatively, modules OSC type requires higher skill quantities than panels, for all the six skill categories analysed. Onsite and offsite skill requirements vary for different OSC types. Additionally, complex, non-linear relationships were recognised between OSC types and the utilisation of their skills. This research presents unique OSC skill prediction models that can provide early-stage advice to policymakers, project planners and manufacturers on OSC skill requirements. It also provides a novel methodology to develop predictive models for specific industry scenarios that have non-linear and complex relationships.

A Multi-Criteria Decision-Making Model for Selecting the Best Project Delivery Systems for Offsite Construction Projects

Off-site construction (OSC) is an innovative construction method that transfers most of the site-based work to a more controlled environment. Construction waste minimization, speedy schedules, higher sustainability, and better quality are some of the perceived benefits of OSC. Therefore, significant research attention has been given to OSC. However, minimal research attention has been given to procurement management in OSC, which could impact its pace of adoption. Existing studies on the procurement methods of OSC projects have overlooked several criteria related to OSC that impact the selection of the appropriate procurement methods (i.e., design-build, construction management, etc.). In addition, the literature lacks decision-making tools to assist OSC practitioners in selecting the appropriate procurement method. In this regard, this study contributes to the body of knowledge by (1) identifying the criteria that impact the selection of OSC procurement methods; (2) developing a multi-criteria decision-making (MCDM) model to select the appropriate OSC procurement methods. The developed MCDM model uses a hybrid approach of analytic network process (ANP) and evidential reasoning (ER). The ANP, which considers the interdependencies among the collected OSC procurement criteria, is used to calculate the relative importance weights through questionnaire surveys. The ER method evaluates various OSC procurement methods in accordance with the criteria importance weights. The results indicate that project quality, cost control, and funding arrangement are the prominent selection factors. On the other hand, the model reveals that the integrated project delivery (IPD) and construction management (CM) methods have the highest utility scores. The MCDM model has been validated by comparing the results with similar studies. The present study could assist OSC practitioners in selecting the appropriate procurement method for OSC projects.

Key Factors Affecting Labor Productivity in Offsite Construction Projects

Key Factors Affecting Labor Productivity in Offsite Construction Projects

Organizational Elements and Collaborative Organizational Citizenship Behavior in Off-Site Construction Projects: Configurational Approach

Organizational Elements and Collaborative Organizational Citizenship Behavior in Off-Site Construction Projects: Configurational Approach

BIM-Based Management System for Off-Site Construction Projects

Offsite construction (OSC) is one of the alternative methods for the various challenges that the construction sector faces today. This study developed a management system based on building information modeling (BIM) to execute OSC projects successfully. Because OSC differs from the conventional onsite building method, the authors studied and analyzed several project cases and interviewed the participants and stakeholders. The OSC method has unique characteristics in the aspects of the projects’ location and time, production process, flow, method, facility, and environment. Moreover, before the system development, we analyzed the OSC project management, usability, and system requirements. These requirements were turned into a BIM-based system following a waterfall model, with six management menus: drawing, schedule, production, logistics, installation and progress monitoring, and progress payment. This study implemented each menu’s vital functions within the system more effectively due to the BIM-based technological features, such as object-oriented data processing, visualization, high interoperability, linkage, and integration. The developed system was applied to four projects. The test resulted in a streamlined work process, improved activity, and less input time and workload than in a non-BIM-based management environment. These findings indicated that the proposed BIM-based system enabled OSC project management to perform better.

Deep Learning-Based PC Member Crack Detection and Quality Inspection Support Technology for the Precise Construction of OSC Projects

Recently, the construction industry has benefited from the increased application of smart construction led by the core technologies of the fourth industrial revolution, such as BIM, AI, modular construction, and AR/VR, which enhance productivity and work efficiency. In addition, the importance of “Off-Site Construction (OSC)”, a factory-based production method, is being highlighted as modular construction increases in the domestic construction market as a means of productivity enhancement. The problem with OSC construction is that the quality inspection of Precast Concrete (PC) members produced at the factory and brought to the construction site is not carried out accurately and systematically. Due to the shortage of quality inspection manpower, a lot of time and money is wasted on inspecting PC members on-site, compromising inspection efficiency and accuracy. In this study, the major inspection items to be checked during the quality inspection are classified based on the existing PC member quality inspection checklist and PC construction specifications. Based on the major inspection items, the items to which AI technology can be applied (for automatic quality inspection) were identified. Additionally, the research was conducted focusing on the detection of cracks, which are one of the major types of defects in PC members. However, accurate detection of cracks is difficult since the inspection mostly relies on a visual check coupled with subjective experience. To automate the detection of cracks for PC members, video images of cracks and non-cracks on the surface were collected and used for image training and recognition using Convolutional Neural Network (CNN) and object detection, one of the deep learning technologies commonly applied in the field of image object recognition. Detected cracks were classified according to set thresholds (crack width and length), and finally, an automated PC member crack detection system that enables automatic crack detection based on mobile and web servers using deep learning and imaging technologies was proposed. This study is expected to enable more accurate and efficient on-site PC member quality inspection. Through the smart PC member quality inspection system proposed in this study, the time required for each phase of the existing PC member quality inspection work was reduced. This led to a reduction of 13 min of total work time, thereby improving work efficiency and convenience. Since quality inspection information can be stored and managed in the system database, human errors can be reduced while managing the quality of OSC work systematically and accurately. It is expected that through optimizing and upgrading our proposed system, quality work for the precise construction of OSC projects can be ensured. At the same time, systematic and accurate quality management of OSC projects is achievable through inspection data. In addition, the smart quality inspection system is expected to establish a smart work environment that enables efficient and accurate quality inspection practices if applied to various construction activities other than the OSC projects.

Design for Manufacturing and Assembly (DfMA) Checklists for Off-Site Construction (OSC) Projects

Off-Site Construction (OSC), which has the advantage of improving construction productivity, is being spotlighted as a solution to the limitations of conventional construction production methods. Despite the need for, and various advantages of, the introduction and utilization of OSC, however, several issues remain, such as design errors and reduction in design completeness, due to the lack of experience and expertise of project participants, as well as improper consideration of production environment and technical constraints. To resolve these issues, it is necessary to develop an optimal design plan that conforms to the OSC manufacturing environment and manufacturing efficiency; thus, there have been ongoing efforts in the construction industry to introduce Design for Manufacturing and Assembly (DfMA), to derive the optimal design plans for OSC projects. Some studies related to the application of DfMA to OSC have been conducted, however they neglected to present a checklist for reviewing the optimality of OSC design plans. This study has therefore developed an OSC–DfMA checklist, to review the optimality of design plans for OSC projects, by listing optimal design goals for OSC projects, the OSC process, and DfMA principles. This study utilized the systematic literature review, structured interview, and content validity analysis methods to develop the OSC–DfMA checklist presented herein. The developed OSC–DfMA checklist will be applicable to reviewing the optimality of the OSC design plans.

Requirements Analysis for Development of Off-Site Construction Project Management System: Focusing on Precast Concrete Construction

There has been increasing interest in the off-site construction (OSC) method in response to issues such as stagnant labor productivity, shortage of skilled workers, challenging site management, heightened safety and health-related regulations, and the push for carbon neutrality. Although efficient performance of an OSC project requires development of management techniques, and application of a management system that reflects the characteristics of the OSC projects, related technologies remain in their infancy. In this study, targeting precast concrete (PC) construction, which is one of the representative construction types of the OSC method, we derive the characteristics of OSC project management in six aspects: production place and time, production process, production method of construction, production method, production entity and facilities, and production environment. Based on this result, we further derived the requirements for developing an OSC project management system. Furthermore, based on the derived requirements, we constructed a system development scenario for the establishment of an installation plan and shipment requests. The managerial characteristics and requirements of the OSC project, presented in this study, provide the theoretical basis for developing OSC project management techniques, as well as guidance for the development of the OSC project management system in the future.

Operations management concepts applied to offsite construction

The Architecture Engineering and Construction (AEC) industry has been criticized for low productivity, lack of innovations, damage to the environment, lack of improvement. Several innovations have emerged to address these problems and, in this paper, the relationship between operations management (OM) and offsite construction will be discussed. The purpose of this paper is to present a proposal for the application of OM concepts in offsite construction. A research method based on the assumption that construction processes can be analyzed as production systems will be used. The resulting proposal consists of the exploration of potential applications, benefits, and barriers of OM in offsite construction based on the current experience of OM in manufacturing processes. A thorough discussion about the implications of this proposal in a project and supply chain levels are presented. The most important conclusions were related to the need for applying OM concepts in offsite construction projects and the need for more research in this direction to prove the proposed proposal.

A systematic review of quality management of offsite construction

Offsite Construction (OSC) continues to gain popularity for faster, safer, cheaper and more sustainable construction project delivery. An improved quality performance is a chief selling point in the advocacy for the widespread adoption of OSC. Paradoxically, quality issues that arise in OSC projects can be extremely costly. However, quality management (QM) is underexplored in the growing OSC literature. This paper critically reviews the QM of OSC literature to uncover the state-of-the-art and proffer recommendations for future research. 38 articles, selected from Scopus and Web of Science, published from 2009 to 2021 and distributed across 20 journals, were selected through a systematic literature review supplemented by a snowball search. An overview of QM of OSC research is provided based on the yearly distribution of articles, country/territory of affiliation, journal sources, OSC types, project life cycle stages and technologies utilised. The findings revealed a growing interest in the sub-domain. The articles were categorised under six topics: post-production quality assessment, rework and defect management, quality risk management, process improvement, requirements management and quality performance factors. This paper also proposes future research directions based on the prevailing knowledge gaps.

Linking Network Embeddedness and Team Members’ Informal Learning Effectiveness in Off-Site Construction Projects: An Opportunity–Motivation–Ability Perspective

Linking Network Embeddedness and Team Members’ Informal Learning Effectiveness in Off-Site Construction Projects: An Opportunity–Motivation–Ability Perspective

Automated Generation of Precast Concrete Slab Stacks for Transportation in Offsite Construction Projects

Automated Generation of Precast Concrete Slab Stacks for Transportation in Offsite Construction Projects

Quality Control for Offsite Construction: Review and Future Directions

The quality of building products is vital for the safety of construction and building occupants. The application of off-site construction (OSC) has been increasing in the industry, one of the reasons being its potential for improving project quality. Yet, various quality problems have been reported, such as cracks and air pockets of prefabricated components, sleeve grouting noncompactness in key nodes, which hinders the development of the OSC sector. It is urgent to carry out quality control (QC) for OSC projects. Substantial research efforts have thus been devoted to these topics in recent decades, resulting in a certain amount of literature regarding QC for OSC. The objective of this study is to conduct a state-of-the-art review of QC for OSC projects to deeply understand its knowledge gaps and future research directions. An integrated review method was used to carry out bibliometric analysis and in-depth qualitative content analysis based on selecting targeted articles. Results show that the identified knowledge gaps include: (1) OSC lacks suitable QC rules, (2) QC means for OSC is out of date, (3) QC information technology for OSC is immature, and (4) existing limitation connotation of QC for OSC. Finally, based on the identified knowledge gaps, corresponding future research directions were suggested, including quality risk transmission control for OSC, supply chain quality management for OSC projects, BIM-based quality data management for OSC, blockchain technology and quality traceability for OSC, and performance and assessment model of QC for OSC. This research contributes to an in-depth and comprehensive understanding of QC for OSC, which offers valuable implications for the quality improvement of the OSC industry.

Development and Application of an Integrated Management System for Off-Site Construction Projects

The off-site construction (OSC) method has attracted the interest of experts to resolve productivity stagnation and lack of skilled workforce and to reduce greenhouse gas emissions in the construction industry. Due to the unique characteristics of OSC projects, wherein building elements are produced in a factory, transported, and installed in the field, a management approach that differs from the management techniques of previous construction projects is required. Accordingly, with this study, we examined the characteristics of OSC projects and derived key management items through literature review, case analysis, and expert meetings to develop an integrated management system for OSC projects (OSC-IMS). The proposed system, OSC-IMS, integrates the entire supply chain of the OSC project. It includes the following functions: drawing management, scheduling and planning, site installation planning, production planning, production monitoring, shipping and transportation, delivery and inspection, site installation monitoring, and progress payment management. To verify the applicability and effectiveness of OSC-IMS, it was implemented in four projects. The application of the system to the case studies demonstrated the improvements in work efficiency and accuracy and decreased waste time in every work step. The findings indicate that the system can enhance project performance. This study contributes to the identification of the features and key elements of OSC management such that these factors can be linked with managing system development. This work describes the overall effect of the proposed system on real projects.

Development Strategy Optimization for Off-Site Construction Projects: Synergy of the Government and Developers

Development Strategy Optimization for Off-Site Construction Projects: Synergy of the Government and Developers